Obstacle Detection for Intelligent Transportation Systems Using Deep Stacked Autoencoder and k -Nearest Neighbor Scheme

Obstacle detection is an essential element for the development of intelligent transportation systems so that accidents can be avoided. In this paper, we propose a stereovision-based method for detecting obstacles in urban environment. The proposed method uses a deep stacked auto-encoders (DSA) model...

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Vydané v:	IEEE sensors journal Ročník 18; číslo 12; s. 5122 - 5132
Hlavní autori:	Dairi, Abdelkader, Harrou, Fouzi, Ying Sun, Senouci, Mohamed
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	IEEE 15.06.2018
Predmet:	autonomous vehicles Clustering algorithms deep learning intelligent transportation systems Kernel Machine learning Machine learning algorithms Obstacle detection Partitioning algorithms Roads Sensors
ISSN:	1530-437X, 1558-1748
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